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Network Metrics Requirements and Usage for WP1

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Network Metrics Requirements and Usage



for WP1



Tiziana Ferrari

Tiziana.Ferrari@cnaf.infn.it









Tiziana Ferrari Network Metrics Requirements and Usage for WP1 1

Applicability examples



• Integration of network info into the scheduling policy:



– To define the most suitable Storage Element for one or more

Computing Elements



• Triggering of data transfers



– To gather in a single Storage Element portions of data sets

partioned among several Ses



• List of applications to be developed further…



Tiziana Ferrari Network Metrics Requirements and Usage for WP1 2

Network information

• CloseSE attribute:

– CloseSE = {(closeness1, SE1), …, (closenessn, SEn)}

• closeness(CE, SE) = max 0
– Closeness varies in [0,1]

– 0 = SE unreachable

– 1 = SE on the same LAN

• Definitions

– r: Round Trip Time, Rmax: max RTT,

– ploss: packet loss frequency;

– th: throughput; thmax: maximum throughput



• closenessi,j (ploss ,r,th) = 0 if ploss  0

• closenessi,j (ploss ,r,th) = th / thmax  r/ rmax where 0 < < 1

otherwise



Tiziana Ferrari Network Metrics Requirements and Usage for WP1 3

Closeness i,j(p,th,r)









Fig 1: alpha = 1/2 Fig 2: alpha = 1/10



Tiziana Ferrari Network Metrics Requirements and Usage for WP1 4

Triggering of data transfers

• Problem statement:

– Input data requested by a given job running on CE is partioned and

portions are stored in different SEi

– Input data needs to be gathered in a single SE and the most appropriate

one has to be selected

– Selection creteria:

• Amount of data in each SEi

• Network distance between two SE

• Closeness of SEi to CE under consideration



• SE is the selected Storage Element for acomputing element CE iff:

SE = SEi iff D(SEi) = minj  D(SEj) 

where D(SEi) is a SE Distance function.







Tiziana Ferrari Network Metrics Requirements and Usage for WP1 5

SE Distance function D

• CASE 1: data in each SEi not known, SEi equivalently distant to CE

– D(SEi) =  1 j n, j i closeness(SEi , SEj )





• CASE 2: SEi equivalently distant to CE

– D(SEi) = max/ i *  1 j n, j i closeness(SEi , SEj )* max/ i

– i : amount of data in each Sei

– max: amount of data requested by a given job



• CASE 3:

– D(SEi) =  closeness(CE, SEi) *max/ i *  1 j n, j i

closeness(SEi , SEj )

– : constant in ]0,1]



Tiziana Ferrari Network Metrics Requirements and Usage for WP1 6



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